Analisis Tingkat Kualitas E-learning menggunakan Metode Webqual 4.0 dan Importance Performance Analysis (IPA)

Authors

  • Badri Yusuf Program Studi Teknik Informatika, Universitas Islam Negeri Sultan Syarif Kasim Riau
  • Fitri Insani Program Studi Teknik Informatika, Universitas Islam Negeri Sultan Syarif Kasim Riau
  • Muhammad Affandes Program Studi Teknik Informatika, Universitas Islam Negeri Sultan Syarif Kasim Riau
  • Novri Yanto Program Studi Teknik Informatika, Universitas Islam Negeri Sultan Syarif Kasim Riau
  • Teddie Darmizal Program Studi Teknik Informatika, Universitas Islam Negeri Sultan Syarif Kasim Riau

DOI:

https://doi.org/10.29408/edumatic.v7i1.14059

Keywords:

e-learning, importance performance analysis, webqual

Abstract

The quality of an academic institution is influenced by its website. E-learning, as a type of website used for learning, offers flexible learning opportunities. In order to enhance the effectiveness of e-learning services, it is necessary to evaluate and identify areas for improvement. This research aims to evaluate the quality of learning using the webqual 4.0 method and Importance Performance Analysis (IPA) to determine gaps and prioritize areas for future improvement. The variables examined in this study include usefulness, information quality, and service interaction quality. A qualitative descriptive design was employed, and data suitability was analysed using the webqual and IPA methods. The research data, consisting of numerical values, was collected through interviews and questionnaires administered to faculty members and students via google form. The evaluation scores for usefulness, information quality, and service interaction quality were found to be 72,9%, 75%, and 74,35%, respectively, indicating good quality. The gap analysis revealed a value of -0,07, suggesting that the e-learning website does not fully meet user expectations. The IPA results showed that quadrants III and IV require improvement due to their low performance, as this can affect the level of importance attributed by users to those attributes.

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Published

2023-06-20